Tsunami Inundation Modeling: Sensitivity of Velocity and Momentum Flux to Bottom Friction With Application to Building Damage at Seaside, Oregon

Park, Hyoungsu; Wiebe, Dane M.; Cox, Daniel T.; Cox, Katherine

doi:10.9753/icce.v34.currents.1

Cited by 10 publications

(11 citation statements)

References 10 publications

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“…Park et al (2013) compare simulated depth, velocity and momentum flux values to experimental results, and Park et al (2014) conduct a sensitivity analysis of the same TIMs to friction coefficient and modelling software. Both studies find that where changes in simulation parameters may lead to small changes in depth, changes in velocity and momentum flux can be much greater (a 15 % change in depth was reported to correspond to a change in velocity and momentum flux of 95 and 208 %, respectively).…”

Section: Assessment Of Construction Response and Inundation Variablesmentioning

confidence: 99%

“…However, this does not account for alternative estimations such as equivalent hydrostatic methods (MLIT 2011), bore impact (Robertson and Riggs 2011) or changes in flow regime (Qi et al 2014). Park et al (2014) compare damage estimates for a case study town in the USA using fragility functions for depth, velocity and momentum flux, concluding that velocity and momentum flux provide the most realistic damage estimates, though this is only based on a qualitative visual assessment of damage locations and the authors acknowledge that this conclusion must be verified with field data.…”

Section: Introductionmentioning

confidence: 99%

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A proposed methodology for deriving tsunami fragility functions for buildings using optimum intensity measures

et al. 2016

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Tsunami fragility curves are statistical models which form a key component of tsunami risk models, as they provide a probabilistic link between a tsunami intensity measure (TIM) and building damage. Existing studies apply different TIMs (e.g. depth, velocity, force etc.) with conflicting recommendations of which to use. This paper presents a rigorous methodology using advanced statistical methods for the selection of the optimal TIM for fragility function derivation for any given dataset. This methodology is demonstrated using a unique, detailed, disaggregated damage dataset from the 2011 Great East Japan earthquake and tsunami (total 67,125 buildings), identifying the optimum TIM for describing observed damage for the case study locations. This paper first presents the proposed methodology, which is broken into three steps: (1) exploratory analysis, (2) statistical model selection and trend analysis and (3) comparison and selection of TIMs. The case study dataset is then presented, and the methodology is then applied to this dataset. In Step 1, exploratory analysis on the case study dataset suggests that fragility curves should be constructed for the sub-categories of engineered (RC and steel) and nonengineered (wood and masonry) construction materials. It is shown that the exclusion of buildings of unknown construction material (common practice in existing studies) may introduce bias in the results; hence, these buildings are estimated as engineered or nonengineered through use of multiple imputation (MI) techniques. In Step 2, a sensitivity analysis of several statistical methods for fragility curve derivation is conducted in order to select multiple statistical models with which to conduct further exploratory analysis and the TIM comparison (to draw conclusions which are non-model-specific). Methods of data aggregation and ordinary least squares parameter estimation (both used in existing studies) are rejected as they are quantitatively shown to reduce fragility curve accuracy and increase uncertainty. Partially ordered probit models and generalised additive models 123Nat Hazards (2016) 84:1257-1285 DOI 10.1007/s11069-016-2485 (GAMs) are selected for the TIM comparison of Step 3. In Step 3, fragility curves are then constructed for a number of TIMs, obtained from numerical simulation of the tsunami inundation of the 2011 GEJE. These fragility curves are compared using K-fold crossvalidation (KFCV), and it is found that for the case study dataset a force-based measure that considers different flow regimes (indicated by Froude number) proves the most efficient TIM. It is recommended that the methodology proposed in this paper be applied for defining future fragility functions based on optimum TIMs. With the introduction of several concepts novel to the field of fragility assessment (MI, GAMs, KFCV for model optimisation and comparison), this study has significant implications for the future generation of empirical and analytical fragility functions.

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Section: Assessment Of Construction Response and Inundation Variablesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A proposed methodology for deriving tsunami fragility functions for buildings using optimum intensity measures

et al. 2016

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“…Park et al (2014) compares damage estimates for a case-study town in the USA using fragility functions for depth, velocity, and momentum flux, concluding that velocity and momentum flux provide the most realistic damage estimates, though this is only based on a qualitative visual assessment of damage locations and the authors acknowledge that this conclusion must be verified with field data. are the only empirical study to consider moment of momentum flux in their fragility curves.…”

Section: Summary Of Intensity Parametersmentioning

confidence: 99%

Estimating Tsunami-Induced Building Damage through Fragility Functions: Critical Review and Research Needs

Charvet

Macabuag

Rossetto

2017

Front. Built Environ.

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Tsunami damage, fragility, and vulnerability functions are statistical models that provide an estimate of expected damage or losses due to tsunami. They allow for quantification of risk, and so are a vital component of catastrophe models used for human and financial loss estimation, and for land-use and emergency planning. This paper collates and reviews the currently available tsunami fragility functions in order to highlight the current limitations, outline significant advances in this field, make recommendations for model derivation, and propose key areas for further research. Existing functions are first presented, and then key issues are identified in the current literature for each of the model components: building damage data (the response variable of the statistical model), tsunami intensity data (the explanatory variable), and the statistical model that links the two. Finally, recommendations are made regarding areas for future research and current best practices in deriving tsunami fragility functions (see Discussion, Recommendations, and Future Research). The information presented in this paper may be used to assess the quality of current estimations (both based on the quality of the data, and the quality of the models and methods adopted) and to adopt best practice when developing new fragility functions.

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“…This approach can serve as an indirect measure of structural vulnerability; however, for areas with little or no record of damage caused by tsunami, accurate fragility curves cannot be developed. The concept of using existing fragility curves to determine structural damage probability is new, with major contributions from [7,12,13]. We extend this idea to Imwon Port in Korea by proposing improved numerical models with improved bathymetric resolution to capture flow features at the individual structure level; we also use fragility curves based on an advanced statistical approach and vast building damage data from the 2011 Great East Tsunami in Japan.…”

Section: Discussionmentioning

confidence: 99%

“…Wiebe and Cox [12] estimated building damage and economic loss for Seaside, Oregon caused by a hypothetical tsunami using the inundation based fragility curves of [4]. Park et al [13] used fragility curves based on flow depth, velocity, and momentum flux for establishing probabilistic damage levels and assessing the sensitivity of damage in response to tsunami features in Seaside, Oregon. We present the building damage assessment for Imwon Port to expand and refine the existing research for areas with no post-tsunami damage records.…”

Section: Introductionmentioning

confidence: 99%

Building Damage Assessment Using Scenario Based Tsunami Numerical Analysis and Fragility Curves

Rehman

Cho

2016

Water

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A combination of a deterministic approach and fragility analysis is applied to assess tsunami damage caused to buildings. The area selected to validate the model is Imwon Port in Korea. The deterministic approach includes numerical modeling of tsunami propagation in the East Sea following an earthquake on the western coast of Japan. The model is based on the linear shallow-water equations (LSWE) augmented with Boussinesq approximation to account for dispersion effects in wave propagation, and coastal wave run-up is modeled by non-linear shallow-water equations (NLSWE). The output from the deterministic model comprises inundation depth. The numerical output is used to perform fragility analysis for buildings vulnerable to flooding by tsunamis in the port area. Recently developed fragility curves-based on the ordinal regression method-are used for damage probability estimates. The extent of structural damage in the areas under a tsunami hazard is identified by the numerical modeling of tsunami features. Our numerical model offers high bathymetric resolution, which enables us to capture flow features at the individual structure level and results in improved estimation of damage probability. This approach can serve as a measure of assessing structure vulnerability for areas with little or no records of tsunami damage and provide planners with a better understanding of structure behavior when a tsunami strikes.

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Tsunami Inundation Modeling: Sensitivity of Velocity and Momentum Flux to Bottom Friction With Application to Building Damage at Seaside, Oregon

Cited by 10 publications

References 10 publications

A proposed methodology for deriving tsunami fragility functions for buildings using optimum intensity measures

A proposed methodology for deriving tsunami fragility functions for buildings using optimum intensity measures

Estimating Tsunami-Induced Building Damage through Fragility Functions: Critical Review and Research Needs

Building Damage Assessment Using Scenario Based Tsunami Numerical Analysis and Fragility Curves

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